347 results about "Amplitude distribution" patented technology

The invention provides an optical image encryption method and system based on a partially coherent non-diffracting light beam, and belongs to the technical field of optical encryption and information transmission. Encoding to-be-encrypted image information into the light field cross-spectral density function; the method specifically comprises the following steps: discretizing an image as an expansion coefficient of a power spectral density function at a light source under a pseudo-mode substrate, and constructing a cross spectral density function; a complex amplitude modulation algorithm is adopted to convert light field complex amplitude distribution into a pure phase hologram, the pure phase hologram is loaded to a spatial light modulator, a multi-mode incoherent superposition partially coherent non-diffraction light beam is generated, and the multi-mode incoherent superposition partially coherent non-diffraction light beam interferes with a reference light beam to obtain a light field image; performing coordinate transformation and frequency domain filtering on the light field image to extract a complex coherence degree function; and reconstructing and restoring the original image information in combination with a preset key and a digital inversion algorithm. According to the method, the light beams are constructed based on pseudo-mode superposition, image hidden coding, transmission and decryption are realized by utilizing the characteristics of partially coherent light and non-diffraction light beams, and the method is suitable for optical communication and security information transmission.

The invention discloses a motor rotating speed measuring method, system and equipment based on electromagnetic induction, and belongs to the field of motors. According to the embodiment of the invention, firstly, a magnetostriction resonance signal and an electromagnetic induction signal of a motor rotating shaft are obtained; performing frequency domain conversion on the magnetostrictive resonance signal to obtain magnetostrictive resonance frequency domain characteristics; performing frequency domain conversion on the electromagnetic induction signal to obtain electromagnetic induction frequency domain characteristics; frequency domain energy spectrum fusion reconstruction is carried out on the magnetostriction frequency domain characteristics and the electromagnetic induction frequency domain characteristics based on the frequency band matching relation between the magnetostriction frequency domain characteristics and the electromagnetic induction frequency domain characteristics, and a dual-frequency coupling energy spectrum is generated; and finally, determining the rotating speed of the motor rotating shaft according to the frequency position and amplitude distribution of the energy peak in the dual-frequency coupling energy spectrum, thereby improving the measurement precision of the rotating speed of the motor in a complex environment.

The invention relates to the technical field of industrial equipment management, in particular to an intelligent power equipment inspection system based on artificial intelligence, which comprises a fault mode generation module, a fault detection module, a fault classification module, an inspection feature optimization module and an anomaly prediction and evaluation module. According to the method, the comprehensiveness of equipment state sensing is optimized by collecting the multi-dimensional operation parameters of the power equipment and analyzing the signal amplitude distribution and frequency domain change, the potential fault features are accurately recognized by combining the dynamic feature range and the signal distribution deviation matching, the signal anomaly detection accuracy is improved, and the fault detection accuracy is improved. The method comprises the following steps: extracting differentiated characteristic values of current and temperature signals, optimizing fault type classification, improving the positioning capability of a problem root, dynamically extracting and matching a signal trend, generating an inspection parameter matrix, realizing global dynamic monitoring of an operation state, and predicting a model based on a signal change rate and a time node range. The real-time performance and precision of abnormal trend prediction are improved, and the reliability of equipment operation and maintenance is enhanced.

The embodiment of the invention relates to the technical field of power line system detection, and discloses a power line detection method based on a sound signal, which comprises the following steps: acquiring sound detection information in a current detection scene through a sound acquisition array; identifying and processing the processed sound detection information through a partial discharge pulse identification algorithm to determine partial discharge pulses in the sound detection information, and determining amplitude parameters of each phase interval according to pulse peak characteristics of the partial discharge pulses, generating a corresponding phase-amplitude distribution diagram according to the phase interval and the amplitude parameter; inputting the phase-amplitude distribution diagram into a pre-constructed partial discharge recognition model for recognition to obtain a corresponding partial discharge type recognition result; and outputting a corresponding partial discharge type identification result and a phase-amplitude distribution diagram. The accuracy and efficiency of power line system safety detection can be improved.

The invention provides a high-frequency welded pipe roller wear state monitoring method and device, and relates to the technical field of artificial intelligence and data processing, a holographic sensing system of working condition parameters and physical signals is constructed through synchronous monitoring of a multi-source sensor, and noise spectrum offset is tracked in real time based on time-frequency expression of data in different modes, so that the real-time monitoring of the wear state of a high-frequency welded pipe roller is realized. And an anti-error filtering protection channel is constructed, so that the inherent characteristics of the damage can be effectively captured. In addition, multi-physical field damage characterization information is fused from multiple complementary dimensions of transient impact (instantaneous frequency vector), spectrum complexity (spectral entropy) and amplitude distribution deflection (skewness), more comprehensive and richer state description can be provided, accurate quantitative evaluation of the roller wear level is achieved, and the capacity of real-time monitoring and accurate recognition of the roller wear state is remarkably improved.

The invention relates to the technical field of cable fault testing, in particular to a multi-core cable fault testing system and method, and the method comprises the steps: determining a fault generation coefficient of a target core wire testing current signal based on the difference between periods where all adjacent signal wave crests in the target core wire testing current signal are located and a periodic parameter; determining the composition richness of the target core wire test current signal based on the similarity of related data sets between the target core wire and all other core wires under different voltage conditions and the signal amplitude distribution near any maximum value point in the target core wire test current signal; and performing forward fusion on the composition richness and the fault occurrence coefficient, adjusting a preset initial decomposition interval scale, screening part of component signals for reconstruction, and performing fault detection on the reconstructed signals. According to the invention, accurate analysis of the test current signal is realized, and the accuracy of fault diagnosis is improved.

This disclosure provides methods, devices and systems for encoding data for wireless communication to achieve an amplitude distribution. One implementation includes a method in which probabilistic amplitude shaping is constrained by an energy value and a sequence composition. The implementation may include three phases. In a first phase, the energy value is determined. In a second phase, the sequence composition is determined. In a third phase, the output sequence is determined as constrained by the sequence composition. The methods generate output sequences defining amplitude symbols that are used to encode data for transmission.

The invention relates to the technical field of power equipment monitoring and noise suppression, in particular to a method for removing partial discharge pulse interference noise based on density clustering, and the method comprises the following steps: S1, collecting a noisy discharge signal, and carrying out the preprocessing of the noisy signal; phase-amplitude characteristics of the noisy signals are extracted, and a phase-amplitude distribution spectrogram is formed; s2, performing primary density clustering analysis on data points in the phase-amplitude distribution spectrogram to obtain a preliminary noise point set; s3, performing secondary density clustering analysis on the initial noise point set to obtain a final noise point set; and S4, performing denoising processing on the noisy discharge signal according to the final noise point set, and performing reverse normalization and reconstruction to obtain a denoised effective discharge signal. According to the technical scheme, the noise in the partial discharge signal can be efficiently and accurately recognized and removed, and the error caused by the fact that a threshold value is manually set in a traditional method is avoided.

A TinyMaix-based switch cabinet partial discharge detection and identification algorithm comprises the following steps: designing four typical insulation defect models, and respectively simulating corona discharge, suspension discharge, surface discharge and internal discharge; 200 samples are collected for each insulation defect, a sample set of 800 samples is formed in total, and a phase-resolved partial discharge (PRPD) graph is constructed according to a phase value in combination with a power frequency synchronization signal; the method comprises the following steps: dividing a power frequency sine wave into 360 phase windows, calculating a discharge frequency and a discharge amplitude average value in each phase window, constructing pulse counting distribution # imgabs0 # and average pulse amplitude distribution # imgabs1 #, extracting a probability pwin, a mean value mu and a variance sigma, and further calculating 19 statistical characteristics such as skewness Sk; a mean square error is selected as a loss function in each iteration of model solution, model parameters are updated according to the gradient of the loss function, and model convergence is accelerated; and inputting a partial discharge signal to be detected into the trained model, and outputting a classification result of the signal by the model to realize identification and classification of the partial discharge signal.

The invention relates to the technical field of new energy grid-connected converters, in particular to a disturbance amplitude design method and device for broadband frequency coupling characteristic measurement, and the method comprises the steps: obtaining the noise amplitude distribution data and spectrum characteristic data of a measured grid-connected converter; determining measurement signal values under different frequencies according to the noise amplitude distribution data and the spectral characteristic data, and estimating a signal-to-noise ratio index of broadband frequency coupling characteristic measurement according to the measurement signal values; determining a measurement error distribution range of the broadband frequency coupling characteristic according to the signal-to-noise ratio index, and determining a measurement precision evaluation result of the broadband frequency coupling characteristic according to the measurement error distribution range; and calculating the disturbance amplitude increase multiple of the broadband frequency coupling characteristic measurement according to the measurement precision evaluation result and the expected measurement error index, and designing the disturbance amplitude of the next broadband frequency coupling characteristic measurement based on the disturbance amplitude increase multiple. Therefore, the problems of poor measurement precision, low measurement efficiency and the like in the prior art are solved.

The invention relates to the technical field of image edge analysis, in particular to an automatic leveling and tamping device for a road foundation. The method comprises the following steps: firstly, screening out all suspected uneven areas according to the edge distribution condition in a road foundation grayscale image; calculating brightness difference according to the characteristic that gray values of two side edges of a soil block generated when a road is uneven under the influence of illumination generally have large difference, so as to preliminarily screen out a preferable uneven area; then considering the characteristic that the edge of the soil block is generally not smooth enough, and determining the possibility of the interference region by combining the gradient amplitude distribution uniformity condition and the edge change stability condition of the edge pixel points of the optimized uneven region; therefore, a more accurate tamped uneven area is screened out according to the possibility of the interference area, so that the effect of leveling and tamping the road foundation according to the tamped uneven area is better.

The invention discloses a cooperative control method and system for noise reduction and fire prevention of a transformer substation. The method comprises the following steps: determining the acoustic impedance mutation degree of an original composite board according to the frequency and amplitude distribution of target low-frequency noise of the transformer substation; when the acoustic impedance abrupt change degree exceeds an abrupt change threshold value, optimizing a first physical parameter of the original composite board; the heat flow density of the first composite board obtained through optimization is obtained, and if the heat flow density exceeds a fireproof threshold value, a second physical parameter of the first composite board is optimized; obtaining a noise penetration index of the target low-frequency-band noise in the second composite board obtained through optimization, and if the noise penetration index does not exceed a penetration threshold value, optimizing a third physical parameter of the second composite board; and determining final physical parameters corresponding to the acoustic-thermal performance balance point according to the acoustic impedance distribution and the thermal conductivity distribution of the third composite board obtained through optimization so as to adjust the structure of the third composite board. According to the invention, collaborative optimization of sound absorption frequency band characteristics and fireproof performance can be realized, and both noise reduction and fire prevention can reach an ideal state at the same time.

The present invention relates to the technical field of industrial equipment management, specifically an intelligent power equipment inspection system based on artificial intelligence. The system includes: a fault mode generation module, a fault detection module, a fault classification module, an inspection feature optimization module, and an abnormal prediction and evaluation module. In the present invention, by collecting multi-dimensional operating parameters of power equipment, analyzing the signal amplitude distribution and frequency domain changes, the comprehensiveness of equipment status perception is optimized. Combining the dynamic feature range and signal distribution deviation matching, potential fault features are accurately identified, and the accuracy of signal anomaly detection is improved. By extracting the differential characteristic values of current and temperature signals, the fault type classification is optimized, and the positioning ability of the problem root cause is enhanced. Dynamically extracting and matching signal trends, generating an inspection parameter matrix, and realizing global dynamic monitoring of the operating state. Based on the prediction model of signal change rate and time node range, the real-time performance and accuracy of abnormal trend prediction are improved, and the reliability of equipment operation and maintenance is enhanced.

The invention relates to the technical field of smart power grids, and provides a multi-field coupling-based overhead conductor vibration test method, which comprises the following steps of: constructing a multi-field coupling test environment, and loading an overhead conductor into the constructed multi-field coupling test environment; applying a multidirectional vibration load to the overhead conductor, and collecting vibration response data of the overhead conductor in real time; and calculating an equivalent stress field and equivalent stress amplitude distribution according to the vibration response data acquired in real time, and evaluating the damage state and residual life of each position of the overhead conductor. According to the overhead conductor vibration test method based on multi-field coupling, complex working conditions can be truly simulated, the test accuracy is improved, high-precision multidirectional vibration load loading is realized, high-resolution data acquisition and synchronization are realized, and the damage state and the residual life are accurately evaluated.

The invention discloses a large-scale antenna for RFID (Radio Frequency Identification) tag inventory, which relates to the technical field of wireless communication, extracts channel state information by using a communication link, extracts main characteristics from a sparse channel through a compressed sensing technology, constructs a channel model, effectively captures a signal path, a multi-path attenuation characteristic and noise intensity, and improves the performance of the antenna in a dynamic environment. According to the signal strength and return delay of the tag, dynamically dividing the inventory area, and adjusting the phase and amplitude distribution of the antenna array through real-time feedback, so that the beam coverage is matched with the channel characteristics, and the signal focusing capability of the target area is enhanced; a recurrent neural network (RNN) is introduced to analyze CSI information and feedback signals, multi-path interference and effective signals are separated by learning time sequence features, independent responses of tags are extracted, and the influence of reflected signal interference on tag identification is reduced; the identification success rate of the weak signal label is improved by preferentially processing the label with the weak signal or the shielded label and combining a dynamic recording and alarming mechanism.

The invention provides a carrier modulation method and modulation-demodulation system for an MMC circulation suppressor, and the method comprises the following steps: obtaining MMC operation log data, carrying out the spectrum analysis, and extracting the spectrum amplitude distribution characteristics; identifying a bridge arm circulation condition based on the amplitude distribution characteristics, and further detecting bridge arm load abnormity and unit energy abnormity conditions; identifying a circulating current frequency component according to an energy abnormal condition, performing electric energy quality attenuation detection and initial circulating current position tracing, and determining a circulating current generation mechanism; and finally, based on the risk assessment result and the generation mechanism data, constructing a modulation parameter, and generating an adaptive circulation suppressor carrier modulation strategy. Compared with the prior art, the method has the following beneficial effects: through modulation of the circulating current suppressor, modulation of the circulating current suppressor is more accurate, so that the problems of inaccurate analysis of a bridge arm circulating current generation mechanism and inaccurate analysis of an energy abnormal condition of the MMC unit existing in carrier modulation of a traditional circulating current suppressor are solved.

The invention relates to the technical field of welding seam defect detection, and discloses a welding seam defect detection method, device and equipment based on three-dimensional holographic scanning. Coherent light is used for irradiating a welding seam to be detected, a reference state hologram sequence and a loading state hologram sequence are generated, a phase difference field is calculated, and the deformation gradient is analyzed; marking a first abnormal region and extracting a deformation concentration ratio and a spatial distribution mode, calculating a dominant spatial frequency through space-frequency domain joint analysis, fusing abnormal features, marking a second abnormal region and extracting amplitude distribution and spatial continuity parameters, and performing defect characterization analysis by combining information of the first and second abnormal regions to obtain weld defect detection information. The method has the advantages of high precision, non-contact and real-time monitoring, the accuracy and efficiency of weld defect detection can be effectively improved, and the problem that weld detection is not accurate enough in the prior art is solved.

The invention relates to the technical field of automatic control, in particular to an automatic control method and system for an electrical system component, and the method comprises the steps: obtaining PID control data and a flow monitoring signal; determining a time delay value between the flow monitoring signals according to the correlation between the two flow monitoring signals; a signal fluctuation factor is determined according to the amplitude distribution of a flow monitoring signal of a monitoring point in a short-time window and the amplitude distribution of a flow monitoring signal of a next monitoring point after time delay in the short-time window, and the interference probability is determined by combining the amplitude difference and phase difference of the flow monitoring signals contained in all the short-time windows in a frequency domain. Screening out interference frequency; obtaining a nonlinear error probability according to the distribution of all interference frequencies; and adjusting the proportional gain in the PID control data according to the nonlinear error probability to complete the automatic control of the adjusting type electric valve. The control precision of the adjusting type electric valve during automatic control is improved by supplementing non-linear errors.

The invention belongs to the technical field of sound tweezers, and particularly relates to a particle customization control method based on sound radiation force and torque, and the method comprises the steps: building a needed sound source array, evaluating the stress and torque of a to-be-controlled particle in a sound field, repeatedly adjusting and optimizing the phase and amplitude distribution in an array unit, and obtaining an optimal sound field configuration condition. In this way, the required optimal sound field environment can be determined in advance, so that the optimal control effect on the particles is achieved, and the suspension height and the rotation speed of the particles are accurately controlled. According to the method, particle behaviors can be more accurately regulated and controlled, the control precision is remarkably improved, the adaptability is enhanced, more complex control scenes and particle types can be coped with, and the method is particularly suitable for the situation that customized control particles are needed.

The invention discloses a ferromagnetic resonance detection and prevention method for a voltage transformer, and belongs to the field of voltage transformer fault monitoring. Whether ferromagnetic resonance exists or not is judged mainly according to the ground capacitive reactance of the voltage transformer and the excitation inductive reactance under the rated line voltage, and if yes, the following steps are executed: a bus zero-sequence voltage signal of the voltage transformer is collected and dispersed; performing windowing processing on the discrete signal by adopting a Hanning window; performing fast Fourier transform on the windowed signal to obtain spectrum signal amplitude distribution; and determining the ferromagnetic resonance type according to the spectrum signal amplitude distribution. According to the method, ferromagnetic resonance can be accurately identified and classified, so that the detection efficiency is improved, the system fault risk is reduced, and the impact of resonance on power equipment is reduced.

The invention relates to the technical field of automobile electronic mechanical braking system control, in particular to an electronic mechanical braking system motor control method based on error compensation, which comprises the following steps of: analyzing the difference of each kind of motor data between all adjacent moments within a preset duration before each moment and the amplitude distribution of each kind of motor data in a frequency domain; determining the disturbed degree; determining a coupling correlation index by analyzing the correlation of the disturbances between each type of motor data and all other types of motor data within the preset duration and the interdependence relationship between each type of motor data and all other types of motor data; and the current of the automobile motor at the current moment is controlled. The problem of distortion caused by noise and non-linear interference of a single data source in an electronic mechanical braking system is solved, control deviation and errors caused by multi-physical field coupling are solved, and the accuracy and reliability of motor control are improved.

The invention discloses an optical flux-inductance-energy integrated system and a transmitted waveform design method, and the method comprises the steps: carrying out the MLS modulation and OFDM modulation of an input original signal, obtaining an MLS waveform and an OFDM waveform, carrying out the amplitude distribution of the two waveforms, and combining the two waveforms according to a time sequence to form an MLS-OFDM AC signal; after the alternating current signal is subjected to digital-to-analog conversion, outputting the alternating current signal according to a set driving peak-to-peak value voltage, superposing a direct current component in the alternating current signal so as to carry out alternating current and direct current amplitude distribution, and outputting an analog electric signal; the transmitter converts analog electric signals into optical signals, and the optical signals are simultaneously connected with the information decoding module, the sensing processing module and the energy collecting module. According to the hybrid MLS-OFDM waveform design scheme combining alternating-current amplitude distribution and alternating-current and direct-current amplitude distribution, flexible balance among communication, perception and energy collection performance in an optical flux-inductance-energy integrated system is achieved, the complexity of the system can be reduced, and the system is made to be lighter and more compact.

The invention discloses an ultrasonic testing device and method for the elastic constant Cij and crystal orientation of a single crystal material or workpiece. A special water immersion ultrasonic testing system used in the ultrasonic testing device comprises a manipulator, a water tank, a probe frame, a sample table and a probe, wherein the probe frame is connected with the tail end clamping device of the manipulator or the probe frame is the tail end clamping device of the manipulator; the sample table for placing a to-be-tested sample is positioned in the water tank; the probe is arranged on the probe frame; three-dimensional ultrasonic signals of various wave modes are excited in a workpiece, scanning signals of the three-dimensional ultrasonic signals are received, an omnidirectional sound time amplitude distribution image under polar coordinates is constructed according to the scanning signals, an ultrasonic anisotropic propagation actual sound field image is obtained, and ultrasonic sound velocities in all directions of a single crystal material are obtained through morphological methods such as image processing. And dual measurement of the elastic constant Cij and the crystal orientation of the single crystal material or the workpiece is realized through an inversion algorithm. According to the method, the elastic modulus and the crystal orientation of the single crystal material can be accurately and rapidly obtained on the premise that the crystal orientation does not need to be predicted, conditions and steps are simplified, and the testing time is shortened.

The invention relates to the technical field of data processing, in particular to a three-dimensional displacement high-precision monitoring method and system for a seismic isolation support, and the method comprises the steps: obtaining acceleration data of the seismic isolation support in different axial directions and a spectrogram of each axial direction within a preset time period; according to the amplitude distribution condition of each frequency in each axial spectrogram, screening out a seismic main frequency, and according to the amplitude proportion condition of the seismic main frequency in each axial spectrogram, obtaining a relative energy value in each axial direction; correcting the acceleration data of each axial direction according to the correlation between the acceleration data of each axial direction and the acceleration data of other axial directions in combination with the distribution condition and the relative energy value of the acceleration data of each axial direction to obtain corrected data of each axial direction; and determining the three-dimensional displacement data of the shock insulation support based on the integral result of each axial correction data. According to the invention, other interference components can be effectively inhibited, and the monitoring precision of the seismic isolation support displacement data is improved.

The invention relates to the technical field of signal processing, in particular to a pipeline guided wave signal processing method and system. The method comprises the following steps: acquiring a multi-channel ultrasonic guided wave signal through a sensor array circumferentially arranged around a pipeline, and converting the multi-channel ultrasonic guided wave signal into a frequency domain response matrix; calculating a circumferential amplitude distortion degree based on the power spectrum amplitude distribution of each channel; constructing a modal coupling matrix by combining the circumferential amplitude distortion degree and the theoretical wave number of the ideal pipeline; correcting the standard orthogonal modal matrix to generate a modal projection matrix; and decomposing the frequency domain response matrix by using the projection matrix, and separating a structure echo component and a defect signal component. According to the method, the influence of geometric defects such as ovality deviation is evaluated more accurately, energy exchange between modeling modes is accurately established, and orthogonality hypothesis is corrected; modal energy leakage is inhibited, and the decomposition accuracy is improved; signals are effectively separated, coherent noise interference is solved, and the accuracy and reliability of pipeline defect detection are improved.

The invention discloses a U-Net-based multi-mode wind energy resource monthly scale prediction correction method and system, belongs to the technical field of wind energy resource evaluation and climate numerical value prediction crossing, and is used for correcting monthly scale wind speed output by a climate mode. According to the method, a climate state wind speed field is constructed by utilizing ERA5 reanalysis, and a monthly-scale 10m wind speed anomaly is calculated to serve as a correction reference; monthly-scale historical return data of a plurality of dynamic climate modes are obtained, 10m wind speed and multilayer meteorological elements are extracted, unified interpolation and standardization are carried out, and a sample set is formed; a U-Net correction model with a coding and decoding structure is constructed based on a sample set, feature combination and hyper-parameters are optimized through cross validation, and nonlinear mapping from a multi-mode forecast field to an ERA5 distance flat field is learned. And correcting future monthly scale forecast by using the optimal model, generating a wind speed product of which space structure and amplitude distribution are closer to observation, and providing high-credibility wind energy climate information for wind power planning, power generation planning and power grid dispatching.

The disclosure relates to a method and a device for transmitting and receiving a signal by a base station or a terminal in a wireless communication system. Specifically, a method performed by a first device in a wireless communication system includes deriving an amplitude scaling factor based on a comparison between amplitude distribution of a pilot signal corresponding to a first time resource domain and the amplitude distribution of a data signal corresponding to a second time resource domain; and transmitting, to a second device, a physical channel including the pilot signal and the data signal and the amplitude scaling factor, wherein the pilot signal is transmitted with a power determined based on the amplitude scaling factor, and power compensation for the data signal is based on the amplitude scaling factor.

The application relates to the technical field of computer vision, in particular to a jujube tree disease and pest identification method and system combined with visual technology, which comprises the following steps: extracting a closed edge contour of a disease leaf gray image, and obtaining a contour skeleton of each closed edge contour; based on the graphic features of each contour skeleton, obtaining a to-be-identified region, analyzing the gradient amplitude distribution of the skeleton contour edge and the inside pixel points, the gradient amplitude distribution of the skeleton contour outside pixel points, and obtaining an edge transition value of each to-be-identified region; based on the overall distribution features of the gradient amplitude of all edge pixel points of the skeleton contour of each to-be-identified region, obtaining an edge energy value of each to-be-identified region; determining an edge distinguishing value of each to-be-identified region, and obtaining a disease identification result of each to-be-identified region. The application aims to improve the identification ability of jujube brown spot disease and jujube gray spot disease and improve the identification precision of disease detection.

The invention relates to the technical field of construction quality detection, in particular to a building construction quality automatic detection method and system.The building construction quality automatic detection method comprises the following steps that vertical projection plane coordinates of multiple components in a building fabricated structure are obtained, a horizontal edge vertex coordinate set is selected, and the geometric center of the components is obtained through calculation and averaging; and generating a component positioning center vector group according to the component number sequence connection points. According to the method, through extraction of vertical projection coordinates of the components, construction of a positioning center vector, establishment of sequence expression of the position relation between the components, judgment of the consistency of the offset difference change rate and the included angle, continuous offset trend extraction, extraction of the gravity center of the components in the section, calculation of the deviation degree of a connecting line to a theoretical axis, and reflection of the overall offset trend of the component section. And identifying the system characteristics of the error according to the offset consistency and the amplitude distribution. According to the process, the component position, direction and aggregation offset characteristics are integrated in a serialization, vectorization and gravity center weighting mode, and the capacity of trend recognition and cluster error judgment is improved.

The invention discloses a partial discharge acoustic imaging detection positioning method and system, a medium and a product, and relates to the field of electrical engineering, and the method comprises the steps: obtaining a sound signal collected by a microphone array, and a video image collected by a camera; detecting an energy accumulation value of a plurality of sound sources in the sound signal within a preset duration; marking the sound source with the energy accumulation value exceeding a preset threshold value as a partial discharge sound source; determining position coordinates of a partial discharge sound source; according to sound characteristics of the partial discharge sound source, the discharge severity is evaluated, and the sound characteristics at least comprise frequency characteristics and amplitude distribution; mapping the position coordinates of the partial discharge sound source to the corresponding position of the video image to obtain a partial discharge sound imaging positioning map, and displaying the discharge severity of the partial discharge sound source in the partial discharge sound imaging positioning map. By implementing the method, the accuracy and precision of partial discharge acoustic imaging detection and positioning can be improved.